Probabilistic Modeling

Matthew F. Dixon, Igor Halperin and Paul Bilokon
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Matthew F. Dixon: Illinois Institute of Technology, Department of Applied Mathematics
Igor Halperin: New York University, Tandon School of Engineering
Paul Bilokon: Imperial College London, Department of Mathematics

Chapter Chapter 2 in Machine Learning in Finance, 2020, pp 47-80 from Springer

Abstract: Abstract This chapter introduces probabilistic modeling and reviews foundational concepts in Bayesian econometrics such as Bayesian inference, model selection, online learning, and Bayesian model averaging. We then develop more versatile representations of complex data with probabilistic graphical models such as mixture models.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-41068-1_2

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DOI: 10.1007/978-3-030-41068-1_2

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